Evidence map›Paper›PMID 32787849›Full record

ArticleBMC medical informatics and decision making2020

Validation of an electronic coding algorithm to identify the primary indication of orthopedic surgeries from administrative data.

John C Giardina, Thomas Cha, Steven J Atlas, Michael J Barry, Andrew A Freiberg, Lauren Leavitt, Felisha Marques, Karen Sepucha

Open access · goldAbstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in BMC medical informatics and decision making, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.

0numbers the graph read from it
0cells of the map it votes in
6citing papers in PubMed
0.7field-weighted citation impact, top 25% of its field
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

6 citing papers in PubMed, 6 citations in OpenAlex.

  1. Article
  2. Article
  3. Article
  4. Article
  5. Article
  6. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

8 authors at 2 institutions in 1 country.

John C GiardinaCenter for Health Decision Science, Harvard T.H. Chan School of Public Health, 718 Huntington Avenue, Boston, MA, 02115, USA. jgiardina@g.harvard.edu.ORCID 0000-0002-6618-1671
Thomas ChaDepartment of Orthopaedic Surgery, Massachusetts General Hospital, Boston, MA, USA.
Steven J AtlasHarvard Medical School, Boston, MA, USA.
Michael J BarryHarvard Medical School, Boston, MA, USA.
Andrew A FreibergDepartment of Orthopaedic Surgery, Massachusetts General Hospital, Boston, MA, USA.
Lauren LeavittDivision of General Internal Medicine, Massachusetts General Hospital, Boston, MA, USA.
Felisha MarquesDivision of General Internal Medicine, Massachusetts General Hospital, Boston, MA, USA.
Karen SepuchaHarvard Medical School, Boston, MA, USA.
Harvard University · USMassachusetts General Hospital · US

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundDetermining the primary indication of a surgical procedure can be useful in identifying patients undergoing elective surgery where shared decision-making is recommended. The purpose of this study was to develop and validate an algorithm to identify patients receiving the following combinations of surgical procedure and primary indication as part of a study to promote shared decision-making: (1) knee arthroplasty to treat knee osteoarthritis (KOA); (2) hip arthroplasty to treat hip osteoarthritis (HOA); (3) spinal surgery to treat lumbar spinal stenosis (SpS); and (4) spinal surgery to treat lumbar herniated disc (HD).

methodsConsecutive surgical procedures performed by participating spine, hip, and knee surgeons at four sites within an integrated care network were included. Study staff reviewed electronic medical records to ascertain a "gold standard" determination of the procedure and primary indication status. Electronic algorithms consisting of ICD-10 and CPT codes for each combination of procedure and indication were then applied to records for each case. The primary measures of validity for the algorithms were the sensitivity and specificity relative to the gold standard review.

resultsParticipating surgeons performed 790 procedures included in this study. The sensitivity of the algorithms in determining whether a surgical case represented one of the combinations of procedure and primary indication ranged from 0.70 (HD) to 0.92 (KOA). The specificity ranged from 0.94 (SpS) to 0.99 (HOA, KOA).

conclusionThe electronic algorithm was able to identify all four procedure/primary indication combinations of interest with high specificity. Additionally, the sensitivity for the KOA cases was reasonably high. For HOA and the spine conditions, additional work is needed to improve the sensitivity of the algorithm to identify the primary indication for each case.

Indexed as

AlgorithmsDecision MakingArthroplasty, Replacement, HipArthroplasty, Replacement, KneeElectronicsHumansIntervertebral Disc DisplacementOrthopedic ProceduresOsteoarthritis, HipOsteoarthritis, KneeReproducibility of ResultsSpinal StenosisAlgorithm validationDiagnostic codeElective surgeryElectronic medical recordOrthopedic surgeryProcedure codeShared-decision making

Identifiers

PMID32787849
PMCPMC7425151
OpenAlexW3048704883

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.